Generative AI in the arts and humanities: A bibliometric analysis of global research trends and thematic clusters (2021-2026)
The rapid advancement of generative artificial intelligence (AI) has fundamentally transformed the creation, perception, and societal implications of visual and literary art. The present study presents the first comprehensive bibliometric analysis of SSCI- and A&HCI-indexed scholarship on AI-generated art, drawing on 290 publications retrieved from the Web of Science Core Collection. Bibliometric methods, including performance analysis, Bradford’s law, keyword clustering, and citation analysis, were applied to examine publication trends, core journals, leading authors and institutions, geographical distributions, thematic clusters, and intellectual influence. Results reveal an explosive growth trajectory: from 4 publications in 2021 to 111 in 2025 (CAGR = 129.5%), reflecting a field in rapid institutionalisation. Keyword analysis identifies four thematic clusters: (1) aesthetic perception and human–AI evaluation, (2) generative AI technology and text-to-image systems, (3) societal and ethical implications, and (4) media, journalism, and communication. The h-index of 24 and g-index of 45 indicate a rapidly maturing, though still nascent, evidence base.